Low autocorrelated multi-phase sequences
Statistical Mechanics
2009-11-07 v1 Disordered Systems and Neural Networks
Abstract
The interplay between the ground state energy of the generalized Bernasconi model to multi-phase, and the minimal value of the maximal autocorrelation function, , , is examined analytically and the main results are: (a) The minimal value of is significantly smaller than the typical value for random sequences . (b) over all sequences of length N is obtained in an energy which is about 30% above the ground-state energy of the generalized Bernasconi model, independent of the number of phases m. (c) The maximal merit factor grows linearly with m. (d) For a given N, indicating that for m=N, , i.e. a Barker code exits. The analytical results are confirmed by simulations.
Cite
@article{arxiv.cond-mat/0103185,
title = {Low autocorrelated multi-phase sequences},
author = {Liat Ein-Dor and Ido Kanter and Wolfgang KJinzel},
journal= {arXiv preprint arXiv:cond-mat/0103185},
year = {2009}
}
Comments
4 pages, 4 figures